CIND110 - Data Organization for Data Analysts Assignment

Assignment Task

Section

1. XML Hierarchical Data Model

Questions

1. Retrieve the names of all the cities in the dataset.

2. Retrieve the populations of each city?

3. Retrieve the name and country of all the cities in the document.

4. Retrieve the names of the attractions in Vancouver.

5. What is the name of the city with the Sagrada Familia attraction?

6. How many attractions are there in Sydney?

7. Retrieve the name and description of all the attractions in the second city in the document.

8. Compare by listing the number of cities with a population higher than one million to those with fewer than one million residents.

2. Information Retrieval (IR) Approaches:

1. Write an XQuery script to convert the XML dataset (Cities XML Data.xml) used in Section I to a relational dataset. Save the file as a’Cities CSVData.csv’ document.

2. Read the relational dataset, and apply three different text pre-processing techniques to cleanse the description attribute.

3. Create a unigram TermDocumentMatrix (TDM), then represent it in a matrix format and display its dimension.

4. Using the vectors obtained in the previous question, apply the cosine similarity function and identify which city is most similar to Toronto.

3. Data Mining - Applying Association Rules

The discovery of association rules is a significant data mining technique that links the occurrence of a group of items with a range of values for another set of variables. In this regard, the database is treated as a compilation of transactions, each consisting of a set of items. The dataset below shows ten transactions of fruits and vegetables made by ten customers in a retail store. Your objective as a data analyst is to identify the appropriate association rules among the item sets as specified in the questions provided.

1. Using a minimum support of 50%, apply the Apriori algorithm to this dataset.

2. List all possible association rules that meet the minimum confidence level of 80% or higher for an itemset.

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